scholarly journals Processes controlling aggregate formation and distribution during the Arctic phytoplankton spring bloom in Baffin Bay

Elem Sci Anth ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jordan Toullec ◽  
Brivaëla Moriceau ◽  
Dorothée Vincent ◽  
Lionel Guidi ◽  
Augustin Lafond ◽  
...  
Keyword(s):  
Sea Ice ◽  
Spring Bloom ◽  
Phytoplankton Bloom ◽  
Light Availability ◽  
Open Water ◽  
The Arctic ◽  
Phytoplankton Production ◽  
Baffin Bay ◽  
Migration Pathway ◽  
Phytoplankton Cells

In the last decades, the Arctic Ocean has been affected by climate change, leading to alterations in the sea ice cover that influence the phytoplankton spring bloom, its associated food web, and therefore carbon sequestration. During the Green Edge 2016 expedition in the central Baffin Bay, the phytoplankton spring bloom and its development around the ice edge was followed along 7 transects from open water to the ice-pack interior. Here, we studied some of the processes driving phytoplankton aggregation, using aggregate and copepod distribution profiles obtained with an underwater vision profiler deployed at several stations along the transects. Our results revealed a sequential pattern during sea ice retreat in phytoplankton production and in aggregate production and distribution. First, under sea ice, phytoplankton started to grow, but aggregates were not formed. Second, after sea ice melting, phytoplankton (diatoms and Phaeocystis spp. as the dominant groups) benefited from the light availability and stratified environment to bloom, and aggregation began coincident with nutrient depletion at the surface. Third, maxima of phytoplankton aggregates deepened in the water column and phytoplankton cells at the surface began to degrade. At most stations, silicate limitation began first, triggering aggregation of the phytoplankton cells; nitrate limitation came later. Copepods followed aggregates at the end of the phytoplankton bloom, possibly because aggregates provided higher quality food than senescing phytoplankton cells at the surface. These observations suggest that aggregation is involved in 2 export pathways constituting the biological pump: the gravitational pathway through the sinking of aggregates and fecal pellets and the migration pathway when zooplankton follow aggregates during food foraging.

scholarly journals Temporal evolution of IP25 and other highly branched isoprenoid lipids in sea ice and the underlying water column during an Arctic melting season

Elem Sci Anth ◽  
2019 ◽  
Vol 7 ◽  
Author(s):  
Rémi Amiraux ◽  
Lukas Smik ◽  
Denizcan Köseoğlu ◽  
Jean-François Rontani ◽  
Virginie Galindo ◽  
...  
Keyword(s):  
Sea Ice ◽  
Water Column ◽  
Spring Bloom ◽  
Phytoplankton Bloom ◽  
Change Point Analysis ◽  
The Arctic ◽  
Distribution Data ◽  
Ice Melt ◽  
Point Analysis ◽  
The Impact

In recent years, certain mono- and di-unsaturated highly branched isoprenoid (HBI) alkene biomarkers (i.e., IP25 and HBI IIa) have emerged as useful proxies for sea ice in the Arctic and Antarctic, respectively. Despite the relatively large number of sea ice reconstructions based on IP25 and HBI IIa, considerably fewer studies have addressed HBI variability in sea ice or in the underlying water column during a spring bloom and ice melt season. In this study, we quantified IP25 and various other HBIs at high temporal and vertical resolution in sea ice and the underlying water column (suspended and sinking particulate organic matter) during a spring bloom/ice melt event in Baffin Bay (Canadian Arctic) as part of the Green Edge project. The IP25 data are largely consistent with those reported from some previous studies, but also highlight: (i) the short-term variability in its production in sea ice; (ii) the release of ice algae with high sinking rates following a switch in sea ice conditions from hyper- to hyposaline within the study period; and (iii) the occurrence of an under-ice phytoplankton bloom. Outcomes from change-point analysis conducted on chlorophyll a and IP25, together with estimates of the percentage of ice algal organic carbon in the water column, also support some previous investigations. The co-occurrence of other di- and tri-unsaturated HBIs (including the pelagic biomarker HBI III) in sea ice are likely to have originated from the diatom Berkeleya rutilans and/or the Pleurosigma and Rhizosolenia genera, residing either within the sea ice matrix or on its underside. Although a possible sea ice source for HBIs such as HBI III may also impact the use of such HBIs as pelagic counterparts to IP25 in the phytoplankton marker-IP25 index, we suggest that the impact is likely to be small based on HBI distribution data.

scholarly journals Phytoplankton Bloom Changes under Extreme Geophysical Conditions in the Northern Bering Sea and the Southern Chukchi Sea

2021 ◽  
Vol 13 (20) ◽  
pp. 4035
Author(s):  
Jinku Park ◽  
Sungjae Lee ◽  
Young-Heon Jo ◽  
Hyun-Cheol Kim
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Bering Sea ◽  
Phytoplankton Biomass ◽  
Phytoplankton Bloom ◽  
Chukchi Sea ◽  
Open Water ◽  
The Arctic ◽  
Atmospheric Conditions ◽  
Northern Bering Sea

The northern Bering Sea and the southern Chukchi Sea are undergoing rapid regional biophysical changes in connection with the recent extreme climate change in the Arctic. The ice concentration in 2018 was the lowest since observations began in the 1970s, due to the unusually warm southerly wind in winter, which continued in 2019. We analyzed the characteristics of spring phytoplankton biomass distribution under the extreme environmental conditions in 2018 and 2019. Our results show that higher phytoplankton biomass during late spring compared to the 18-year average was observed in the Bering Sea in both years. Their spatial distribution is closely related to the open water extent following winter-onset sea ice retreat in association with dramatic atmospheric conditions. However, despite a similar level of shortwave heat flux, the 2019 springtime biomass in the Chukchi Sea was lower than that in 2018, and was delayed to summer. We confirmed that this difference in bloom timing in the Chukchi Sea was due to changes in seawater properties, determined by a combination of northward oceanic heat flux modulation by the disturbance from more extensive sea ice in winter and higher surface net shortwave heat flux than usual.

scholarly journals Shells of the bivalve Astarte moerchi give new evidence of a strong pelagic-benthic coupling shift occurring since the late 1970s in the North Water polynya

2020 ◽  
Vol 378 (2181) ◽  
pp. 20190353 ◽  
Author(s):  
Frédéric Olivier ◽  
Blandine Gaillard ◽  
Julien Thébault ◽  
Tarik Meziane ◽  
Réjean Tremblay ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Sea Ice ◽  
Phytoplankton Bloom ◽  
Euphotic Zone ◽  
Ice Cover ◽  
The Arctic ◽  
Phytoplankton Production ◽  
Ice Dynamics ◽  
The North ◽  
Benthic Coupling

Climate changes in the Arctic may weaken the currently tight pelagic-benthic coupling. In response to decreasing sea ice cover, arctic marine systems are expected to shift from a ‘sea-ice algae–benthos' to a ‘phytoplankton-zooplankton’ dominance. We used mollusc shells as bioarchives and fatty acid trophic markers to estimate the effects of the reduction of sea ice cover on the food exported to the seafloor. Bathyal bivalve Astarte moerchi living at 600 m depth in northern Baffin Bay reveals a clear shift in growth variations and Ba/Ca ratios since the late 1970s, which we relate to a change in food availability. Tissue fatty acid compositions show that this species feeds mainly on microalgae exported from the euphotic zone to the seabed. We, therefore, suggest that changes in pelagic-benthic coupling are likely due either to local changes in sea ice dynamics, mediated through bottom-up regulation exerted by sea ice on phytoplankton production, or to a mismatch between phytoplankton bloom and zooplankton grazing due to phenological change. Both possibilities allow a more regular and increased transfer of food to the seabed. This article is part of the theme issue ‘The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning'.

scholarly journals Retrieval of Summer Sea Ice Concentration in the Pacific Arctic Ocean from AMSR2 Observations and Numerical Weather Data Using Random Forest Regression

2021 ◽  
Vol 13 (12) ◽  
pp. 2283
Author(s):  
Hyangsun Han ◽  
Sungjae Lee ◽  
Hyun-Cheol Kim ◽  
Miae Kim
Keyword(s):  
Random Forest ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Open Water ◽  
The Arctic ◽  
Atmospheric Effects ◽  
Sea Ice Concentration ◽  
Air Temperatures ◽  
The Pacific ◽  
Ice Concentration

The Arctic sea ice concentration (SIC) in summer is a key indicator of global climate change and important information for the development of a more economically valuable Northern Sea Route. Passive microwave (PM) sensors have provided information on the SIC since the 1970s by observing the brightness temperature (TB) of sea ice and open water. However, the SIC in the Arctic estimated by operational algorithms for PM observations is very inaccurate in summer because the TB values of sea ice and open water become similar due to atmospheric effects. In this study, we developed a summer SIC retrieval model for the Pacific Arctic Ocean using Advanced Microwave Scanning Radiometer 2 (AMSR2) observations and European Reanalysis Agency-5 (ERA-5) reanalysis fields based on Random Forest (RF) regression. SIC values computed from the ice/water maps generated from the Korean Multi-purpose Satellite-5 synthetic aperture radar images from July to September in 2015–2017 were used as a reference dataset. A total of 24 features including the TB values of AMSR2 channels, the ratios of TB values (the polarization ratio and the spectral gradient ratio (GR)), total columnar water vapor (TCWV), wind speed, air temperature at 2 m and 925 hPa, and the 30-day average of the air temperatures from the ERA-5 were used as the input variables for the RF model. The RF model showed greatly superior performance in retrieving summer SIC values in the Pacific Arctic Ocean to the Bootstrap (BT) and Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI) algorithms under various atmospheric conditions. The root mean square error (RMSE) of the RF SIC values was 7.89% compared to the reference SIC values. The BT and ASI SIC values had three times greater values of RMSE (20.19% and 21.39%, respectively) than the RF SIC values. The air temperatures at 2 m and 925 hPa and their 30-day averages, which indicate the ice surface melting conditions, as well as the GR using the vertically polarized channels at 23 GHz and 18 GHz (GR(23V18V)), TCWV, and GR(36V18V), which accounts for atmospheric water content, were identified as the variables that contributed greatly to the RF model. These important variables allowed the RF model to retrieve unbiased and accurate SIC values by taking into account the changes in TB values of sea ice and open water caused by atmospheric effects.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

Eddy covariance flux measurements of momentum, heat and carbon dioxide in Hudson Bay at the onset of sea ice melt 

2021 ◽  
Author(s):  
Richard Sims ◽  
Brian Butterworth ◽  
Tim Papakyriakou ◽  
Mohamed Ahmed ◽  
Brent Else
Keyword(s):  
Carbon Dioxide ◽  
Gas Exchange ◽  
Sea Ice ◽  
Eddy Covariance ◽  
Open Water ◽  
The Arctic ◽  
Gas Transfer ◽  
Hudson Bay ◽  
Flux Measurements ◽  
Ice Fraction

<p>Remoteness and tough conditions have made the Arctic Ocean historically difficult to access; until recently this has resulted in an undersampling of trace gas and gas exchange measurements. The seasonal cycle of sea ice completely transforms the air sea interface and the dynamics of gas exchange. To make estimates of gas exchange in the presence of sea ice, sea ice fraction is frequently used to scale open water gas transfer parametrisations. It remains unclear whether this scaling is appropriate for all sea ice regions. Ship based eddy covariance measurements were made in Hudson Bay during the summer of 2018 from the icebreaker CCGS Amundsen. We will present fluxes of carbon dioxide (CO<sub>2</sub>), heat and momentum and will show how they change around the Hudson Bay polynya under varying sea ice conditions. We will explore how these fluxes change with wind speed and sea ice fraction. As freshwater stratification was encountered during the cruise, we will compare our measurements with other recent eddy covariance flux measurements made from icebreakers and also will compare our turbulent CO<sub>2 </sub>fluxes with bulk fluxes calculated using underway and surface bottle pCO<sub>2</sub> data. </p><p> </p>

The implications of selected processing methods on satellite altimetry derived sea ice thickness state and trends in the seasonal ice zone

2021 ◽  
Author(s):  
Isolde Glissenaar ◽  
Jack Landy ◽  
Alek Petty ◽  
Nathan Kurtz ◽  
Julienne Stroeve
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Satellite Altimetry ◽  
Region Of Interest ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Baffin Bay ◽  
The Impact

<p>The ice cover of the Arctic Ocean is increasingly becoming dominated by seasonal sea ice. It is important to focus on the processing of altimetry ice thickness data in thinner seasonal ice regions to understand seasonal sea ice behaviour better. This study focusses on Baffin Bay as a region of interest to study seasonal ice behaviour.</p><p>We aim to reconcile the spring sea ice thickness derived from multiple satellite altimetry sensors and sea ice charts in Baffin Bay and produce a robust long-term record (2003-2020) for analysing trends in sea ice thickness. We investigate the impact of choosing different snow depth products (the Warren climatology, a passive microwave snow depth product and modelled snow depth from reanalysis data) and snow redistribution methods (a sigmoidal function and an empirical piecewise function) to retrieve sea ice thickness from satellite altimetry sea ice freeboard data.</p><p>The choice of snow depth product and redistribution method results in an uncertainty envelope around the March mean sea ice thickness in Baffin Bay of 10%. Moreover, the sea ice thickness trend ranges from -15 cm/dec to 20 cm/dec depending on the applied snow depth product and redistribution method. Previous studies have shown a possible long-term asymmetrical trend in sea ice thinning in Baffin Bay. The present study shows that whether a significant long-term asymmetrical trend was found depends on the choice of snow depth product and redistribution method. The satellite altimetry sea ice thickness results with different snow depth products and snow redistribution methods show that different processing techniques can lead to different results and can influence conclusions on total and spatial sea ice thickness trends. Further processing work on the historic radar altimetry record is needed to create reliable sea ice thickness products in the marginal ice zone.</p>

scholarly journals Implications of sea-ice biogeochemistry for oceanic production and emissions of dimethyl sulfide in the Arctic

2017 ◽  
Vol 14 (12) ◽  
pp. 3129-3155 ◽  
Author(s):  
Hakase Hayashida ◽  
Nadja Steiner ◽  
Adam Monahan ◽  
Virginie Galindo ◽  
Martine Lizotte ◽  
...  
Keyword(s):  
Sea Ice ◽  
Water Column ◽  
Dimethyl Sulfide ◽  
Phytoplankton Bloom ◽  
Model Simulation ◽  
Field Measurements ◽  
Sulfur Cycle ◽  
The Arctic ◽  
Model Parameters ◽  
Ocean Ecosystem

Abstract. Sea ice represents an additional oceanic source of the climatically active gas dimethyl sulfide (DMS) for the Arctic atmosphere. To what extent this source contributes to the dynamics of summertime Arctic clouds is, however, not known due to scarcity of field measurements. In this study, we developed a coupled sea ice–ocean ecosystem–sulfur cycle model to investigate the potential impact of bottom-ice DMS and its precursor dimethylsulfoniopropionate (DMSP) on the oceanic production and emissions of DMS in the Arctic. The results of the 1-D model simulation were compared with field data collected during May and June of 2010 in Resolute Passage. Our results reproduced the accumulation of DMS and DMSP in the bottom ice during the development of an ice algal bloom. The release of these sulfur species took place predominantly during the earlier phase of the melt period, resulting in an increase of DMS and DMSP in the underlying water column prior to the onset of an under-ice phytoplankton bloom. Production and removal rates of processes considered in the model are analyzed to identify the processes dominating the budgets of DMS and DMSP both in the bottom ice and the underlying water column. When openings in the ice were taken into account, the simulated sea–air DMS flux during the melt period was dominated by episodic spikes of up to 8.1 µmol m−2 d−1. Further model simulations were conducted to assess the effects of the incorporation of sea-ice biogeochemistry on DMS production and emissions, as well as the sensitivity of our results to changes of uncertain model parameters of the sea-ice sulfur cycle. The results highlight the importance of taking into account both the sea-ice sulfur cycle and ecosystem in the flux estimates of oceanic DMS near the ice margins and identify key uncertainties in processes and rates that should be better constrained by new observations.

scholarly journals Net community production in the bottom of first-year sea ice over the Arctic spring bloom

2017 ◽  
Vol 44 (17) ◽  
pp. 8971-8978 ◽  
Author(s):  
K. Campbell ◽  
C. J. Mundy ◽  
M. Gosselin ◽  
J. C. Landy ◽  
A. Delaforge ◽  
...  
Keyword(s):  
Sea Ice ◽  
Spring Bloom ◽  
The Arctic ◽  
First Year ◽  
Net Community Production ◽  
Community Production

scholarly journals Importance of open-water ice growth and ice concentration evolution: a study based on FESOM-ECHAM6

2015 ◽  
Vol 6 (2) ◽  
pp. 2137-2179
Author(s):  
X. Shi ◽  
G. Lohmann
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Global Climate Model ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Water Ice ◽  
Ice Growth ◽  
Ice Concentration

Abstract. A newly developed global climate model FESOM-ECHAM6 with an unstructured mesh and high resolution is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. A sensitivity experiment is performed which reduces the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting decrease in the Arctic winter sea-ice concentration strongly reduces the surface albedo, enhances the ocean heat release to the atmosphere, and increases the sea-ice production. Furthermore, our simulations show a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the sea ice transport affects the freshwater budget in regions of deep water formation. A warming over Europe, Asia and North America, associated with a negative anomaly of Sea Level Pressure (SLP) over the Arctic (positive phase of the Arctic Oscillation (AO)), is also simulated by the model. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), especially for the Pacific sector. Additionally, a series of sensitivity tests are performed using an idealized 1-D thermodynamic model to further investigate the influence of the open-water ice growth, which reveals similar results in terms of the change of sea ice and ocean temperature. In reality, the distribution of new ice on open water relies on many uncertain parameters, for example, surface albedo, wind speed and ocean currents. Knowledge of the detailed processes is currently too crude for those processes to be implemented realistically into models. Our sensitivity experiments indicate a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system.

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